ABSTRACT
BACKGROUND: High-titer convalescent plasma given early for COVID-19 may decrease progression into a severe infection. Here, we reported a study of serial antibody measurements in patients who received CP at our center and performed a systematic review of randomized trials on CP. METHODS: Our center participated in the Mayo Clinic Expanded Access Program for COVID-19 Convalescent Plasma. Patients diagnosed with COVID-19 by nasopharyngeal polymerase chain reaction at our center between April and August 2020 were included in the study if staffing was available for specimen collection. Through a colloidal gold immunochromatography assay, these patients' IgM and IgG antibody responses were measured at baseline (Day 0) and after transfusion (Day 1, 2, etc.). Donor CP antibody levels were measured as well. RESULTS: 110 serum specimens were obtained from 21 COVID-19 patients, 16 of whom received CP. The median time from developing symptoms to receiving CP was 11 days (range 4-21). In 9 of 14 (64%) cases where both recipient and donor CP antibody levels were tested, donor COVID-19 IgG was lower than that of the recipient. Higher donor antibody levels compared with the recipient (R = 0.71, p < 0.01) and low patient IgG before CP transfusion (p = 0.0108) correlated with increasing patient IgG levels from baseline to Day 1. Among all patients, an increased COVID-19 IgG in the short-term and longitudinally was positively correlated with improved clinical outcomes (ρ = 0.69, p = 0.003 and ρ = 0.58, p < 0.006, respectively). CONCLUSIONS: In a real-world setting where donor CP was not screened for the presence of antibodies, CP in donors might have less COVID-19 IgG than in recipients. An increase in patient antibody levels in the short term and longitudinally was associated with improved clinical outcomes.
ABSTRACT
More than sixty million cases were affected by the novel corona virus around the world till date. The virus has reached more than 200 countries and more than seven lakh people have lost their lives globally so far. To control the spread of this virus many countries have taken extreme measures but still couldn't control the spread. The primary objective of this analysis is to classify the various policy factors adopted by the countries to manage the spread of Covid-19. Our study uses Oxford Covid-19 Government Response Tracker (OxCGRT) dataset and Autoregressive Integrated Moving Average (ARIMA) model as the model for forecasting. The representation is trained using day wise number of infected cases reported in each country from August'2020 to October'2020 and then forecasts the number of infections for five days from 15th November' 2020 to 19th November'2020. We have included 15 countries in our study and analysed 13 factors which includes 8 factors in Containment and Closure policies category, 2 factors in Economic policies category and 3 factors in Health System policies category. We analysed the impact of above factors by comparing the forecasted number of affected people with the actual total diseased cases reported in those five days. The study discovers the fact that out of thirteen policy factors, the countries which concentrated more on policies in economic category during the pandemic have helped in controlling the dissemination of covid-19.